• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1405-1409
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• 2004

This paper is studied new block mode decision algorithm for H.264/AVC. The fast block mode decision algorithm is consist of block range decision algorithm. The block range decision algorithm classifies the block over 8$\times$8 size or below for 16${\times}$16 macroblock to decide the size and type of sub blocks. As the sub blocks of 8$\times$8, 8r4, 4$\times$8 and 4$\times$4, which are the blocks below 8$\times$8 size, include important motion information, the exact sub block decision is required. RDC(RDO cost) is used as the matching parameter for the exact sub block decision. RDC is calculated with motion strength which is the mean value of neighbor pixels of each sub block. The sub block range decision reduces encoding arithmetic amount by 34.62% on the average more than the case not using block range decision. The block mode decision using motion strength shows improvement of PSNR of 0.05[dB].

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.39-46
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• 2013

Recently, the mobile industries grow up rapidly and their performances are improved. So the usage of mobile devices is increasing in our life. Also mobile devices equipped with a high-performance camera, so the image stitching can carry out on the mobile devices instead of the desktop. However the mobile devices have limited hardware to perform the image stitching which has a lot of computational complexity. In this paper, we have proposed improved feature descriptor extraction and matching method for efficient image stitching on mobile environment. Our method can reduce computational complexity using extension of orientation window and reduction of dimension feature descriptor when feature descriptor is generated. In addition, the computational complexity of image stitching is reduced through the classification of matching points. In our results, our method makes to improve the computational time of image stitching than the previous method. Therefore our method is suitable for the mobile environment and also that method can make natural-looking stitched image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6C
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• pp.601-609
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• 2002

The efficient Viterbi decoder that supports full data-rate output of DAB system was proposed. Viterbi decoder consumes lots of computational load and should be designed to be fast specific hardware. In this paper, SST scheme was adopted for Viterbi decoder with puncturing to reduced the power consumption. Puncturing vector tables are modified and re-arranged to be designed by a hardwired logic to save the system area. New re-scaling scheme which uses the fact that the difference of the maximum and minimum of the path metric values is bounded is proposed. The proposed re-scaling scheme optimizes the wordlength of path metric memory and greatly reduces the computational load for re-scaling by controlling MSB of path metric memory. Another saving of computation is done by proposed algorithm for branch metric calculation, which makes use of pre-calculated metric values. The designed Viterbi decoder was synthesized using SAMSUNG 0.35$\mu$ standard cell library and occupied small area and showed lower power consumption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.98-104
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• 2009

Tone injection scheme has been known as one of PAPR(Peak to Average Power Ratio) reduction methods deployable to multi-carrier system like OFDM(Orthogonal Frequency Division Multiplexing). The basic idea in tone injection scheme is to enforce the constellation size larger so that each of original constellation points is mapped into the preassigned distinct points. Along the accomplishment of tone injection, it needs great amount of computations to search out not only an appropriate frequency but a phase. Although there is no loss of transmission rate is expected because of no need to send the overhead, the tone injection scheme has not been preferable due to its enormous computations. To alleviate the amount of complexity, this paper proposes the GA(Genetic Algorithm) based tone injection scheme such that its complexity is reduced comparing with that of the conventional method. The simulation results show that the proposed GA based tone injection scheme approaches the PAPR performance associated with the conventional exhaustive search method at the expense of low computations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.477-487
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• 2017

Multiparty computation (MPC) is a computation technique where many participants provide their data and jointly compute operations to get a computation result. Earlier MPC protocols were mostly depended on communication between the users. Several schemes have been presented that mainly work by delegating operations to two non-colluding servers. Peter et al. propose a protocol that perfectly eliminates the need of users' participation during the whole computation process. However, the drawback of their scheme is the excessive dependence on the server communication. To cater this issue, we propose a protocol that reduce server communication overhead using the proxy re-encryption (PRE). Recently, some authors have put forward their efforts based on the PRE. However, these schemes do not achieve the desired goals and suffer from attacks that are based on the collusion between users and server. This paper, first presents a comprehensive analysis of the existing schemes and then proposes a secure and efficient MPC protocol. The proposed protocol completely eliminates the need of users' participation, incurs less communication overhead and does not need to solve the discrete logarithm problem (DLP) in order to get the computation results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.37-42
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• 2005

It is necessary that Fail-Safe Seaway technology providing a continuous navigation solution though fault of navigation system is occurred in sea. This paper focus on signal processing of GPS receiver, one of receivers using the software radio technology to implement a integrated radio navigation system including satellite-based and ground-based navigation systems. It is difficult to implement the software GPS receivers using a commercial processor bemuse of the heavy computational burden for processing the GPS signals in real time. This paper proposes an efficient multi-bit GPS signal processing scheme to reduce the computational burden for processing the GPS signals in the software GPS receiver. The proposed scheme uses a compression concept of the multi-bit replica signals and patterned look-up table method to generate the correlation value between the GPS signals and the replica signals.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.434-445
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• 2004

Motion Estimation is an essential module in video encoders based on international standards such as H.263 and MPEG. Many fast motion estimation algorithms have been proposed in order to reduce the computational complexity of a well-known full search algorithms(FS). However, these fast algorithms can not work efficiently in DSP processors recently developed for video processing. To solve for this. we propose an efficient motion estimation scheme optimized in the DSP processor like Philips TM1300. A motion vector predictor is pre-estimated and a small search range is chosen in the proposed scheme using strong motion vector correlation between a current macro block (MB) and its neighboring MB's to reduce computation time. An MPEG-4 SP@L3(Simple Profile at Level 3) encoding system is implemented in Philips TM1300 to verify the effectiveness of the proposed method. In that processor, we can achieve better performance using our method than other conventional ones while keeping visual quality as good as that of the FS.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.119-131
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• 2018

The increase of high-resolution spatial data and methodological developments in recent years has enabled a detailed analysis of individual experiences in space and over time. However, despite the increasing availability of data and technological advances, such individual-level analysis is not always possible in practice because of its computing requirements. To overcome this limitation, there has been a considerable amount of research on the use of high-performance, public cloud computing platforms for spatial analysis and simulation. The purpose of this paper is to empirically evaluate the efficiency and effectiveness of spatial analysis in cloud computing platforms. We compare the computing speed for calculating the measure of spatial autocorrelation and performing geographically weighted regression analysis between a local machine and spot instances on clouds. The results indicate that there could be significant improvements in terms of computing time when the analysis is performed parallel on clouds.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.1-8
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• 2021

In this paper, we propose reinforced VGG style network structure for low performance embedded system to classify low resolution infrared image. The combination of reinforced VGG style network structure and global average pooling makes lower computational complexity and higher accuracy. The proposed method classify the synthesize image which have 9 class 3,723,328ea images made from OKTAL-SE tool. The reinforced VGG style network structure composed of 4 filters on input and 16 filters on output from max pooling layer shows about 34% lower computational complexity and about 2.4% higher accuracy then the first parameter minimized network structure made for embedded system composed of 8 filters on input and 8 filters on output from max pooling layer. Finally we get 96.1% accuracy model. Additionally we confirmed the about 31% lower inference lead time in ported C code.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.842-849
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• 2022

With the development of deep learning technology, there are many cases of using DNNs in embedded systems such as unmanned vehicles, drones, and robotics. Typically, in the case of an autonomous driving system, it is crucial to run several DNNs which have high accuracy results and large computation amount at the same time. However, running multiple DNNs simultaneously in an embedded system with relatively low performance increases the time required for the inference. This phenomenon may cause a problem of performing an abnormal function because the operation according to the inference result is not performed in time. To solve this problem, the solution proposed in this paper first reduces the computation by applying the Tucker decomposition to DNN models with big computation amount, and then, make DNN models run in parallel as much as possible in the unit of hidden layer inside the GPU. The experimental result shows that the DNN inference time decreases by up to 75.6% compared to the case before applying the proposed technique.